A Highly Sensitive Wear Debris Sensor Based on Differential Detection

Wear debris in the oil contains a wealth of information about the friction pairs of the mechanical equipment. By analyzing the size and type of wear debris through oil detection technology, condition monitoring and fault diagnosis of mechanical systems can be realized. This article presents an inductive sensor based on differential detection and its signal conditioning circuit, which can detect metal wear debris in the oil. The sensor adopts the structure of two induction coils embedded in one excitation coil. The differential signal is obtained by reverse connecting two induction coils with the same parameters, which can suppress the common-mode interference and eliminate the influence of ambient noise so that the sensor has extremely low noise. Through the designed signal conditioning circuit, the detection signal is phase-sensitive detected, and the information of wear debris is extracted by amplification and filtering. In this article, the sensing principle of the sensor is derived, the spacing between the two induction coils is optimized using the finite-element simulation, and the optimal excitation frequency, detection limit, and detection error of the sensor are investigated through experiments. The experiment results show that the sensor can detect 20- $\mu \text{m}$ iron particles and 130- $\mu \text{m}$ copper particles in a 2-mm flow channel, and the detection error of the sensor is less than 22%. The sensor has the advantages of simple structure and high sensitivity and can be applied to detect metal wear debris in hydraulic oil.